Abstract Efficient animal production involves accurate estimations of fertilizing ability. One key factor is the plasma membrane of the sperm cell, which is actively involved in the cascade of events before oocyte fusion. Many methods are used to analyze the characteristics of this membrane, including partition in aqueous two-phase systems which is an efficient method to analyze sperm surface changes accounting for loss of viability and different functional states. Centrifugal countercurrent distribution (CCCD) analysis can also be used in an aqueous two-phase system to determine the relationship between sperm parameters and in vivo fertility in ewes. In a previous work, we found a significant correlation between two post-CCCD parameters (heterogeneity and recovered viability) and field fertility when the same sample was used after cervical AI. The present study was intended to find out whether the control of several external factors that affect reproductive efficiency is able to increase the correlation coefficient between post-CCCD parameters and fertility. Thus, 90 Rasa aragonesa ewes were controlled on the same farm and received intrauterine inseminations using the same technical equipment. The fertilizing ability of the raw semen and sperm samples selected by a dextran/swim-up process was compared using a low number of spermatozoa per insemination (7 Â 10 7 ) to enhance possible fertility differences. A new post-CCCD parameter was considered; the loss of viability (LV) occurred during the CCCD process. This variable denotes the sperm surviving ability and corresponds to the difference between the total number of viable cells loaded and recovered after the CCCD run. The mean fertility of eight sperm control samples was 60% (range: 25-76%), and there was no significant correlation between standard parameters and in vivo fertility. LV ranged from 2 to 69% (average 27%) and was negatively correlated with fertility (r ¼ À0.914, P < 0.01). Ejaculate heterogeneity (H) ranged from 20 to 47% and was positively, but not significantly, correlated with fertility (r ¼ 0.391). A predictive equation for fertility was deduced by multiple analysis with a very high correlation coefficient (r ¼ 0.967), and level of significance (P < 0.005): predictive fertility PF ¼ 52.546 À 0.594 LV þ 0.665 H. The mean fertility of 13 swim-up selected samples was 63% (range: 25-86%). Again, only parameters derived from the CCCD analysis were highly correlated with fertility, especially LV and H (P < 0.05)
